The use of a neural network (hereinafter, referred to as NN) is generally known as one of the methods of searching for the optimum solution to a set problem. The NN is a network in which models of plural brain cells are arranged, and which is used to find the optimum solution.
Furthermore, several examples of the use of a genetic algorithm (hereinafter, referred to as general GA) are known as another method (for example, see Non Patent Literatures 1 and 2 etc.). General GA is a type of evolutionary computation in which the target of the problem is expressed in the form of a gene, and it makes the gene to be evolved through mating and mutation. General GA is an algorithm that is built on the basis of Darwin's theory of evolution.
However, according to NN, the search method is a linear type steepest descent method, and strongly depends on the search start position, therefore it brings a defect that it converges on a minimum point in the value around the search start position and never getting to the optimum solution or a nearby value in many cases, which is so-called local minimum.
Furthermore, according to the general GA described in the above Non Patent Literature 1 etc., it tends to converge on one specific species only, and It cannot be made to evolve to the optimum solution in many cases, although the situation is different from NN, the problem of local minimum is seen. That is, the types of genes become less in the process of evolution, and convergence occurs on solutions that are far away from the optimum solution and rather than the optimum solution. Furthermore, according to the general GA, when a problem is searched and the solution is found out, the information of a gene, that is, an individual, is biased thus leading to an oligopoly situation where there is no diversity of species. As a result, the gene cluster cannot be applied as is to another problem. Therefore, when dealing with another problem, it becomes necessary to perform reinitialization in order to solve the problem. Thus, for example, if the characteristics of a problem for which an optimum solution is to be found out time series change, the problem cannot be handled promptly.